EYTech S and T-AI-ML senior-GDSN02
About this role
Key Responsibilities
- Lead and execute AI/ML assessments to evaluate current-state analytics, automation, and AI maturity across client organizations.
- Design and drive AI transformation roadmaps aligned with business objectives, identifying opportunities for predictive analytics, intelligent automation, and Generative AI adoption.
- Architect and implement AI/ML solutions leveraging traditional machine learning, NLP, computer vision, and Generative AI technologies.
- Build and optimize machine learning pipelines, model training workflows, feature engineering processes, and deployment architectures.
- Design and implement Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and enterprise AI frameworks.
- Work closely with business stakeholders to gather requirements, define use cases, prioritize opportunities, and establish measurable success criteria.
- Lead proof-of-concepts (PoCs), pilots, and production deployments while ensuring scalability, security, and governance compliance.
- Develop technical documentation including architecture diagrams, implementation plans, AI solution blueprints, and operational runbooks.
- Collaborate with cloud, security, application, and data engineering teams to ensure successful solution delivery.
- Stay current with emerging AI technologies, frameworks, and best practices, and provide strategic recommendations to clients.
Required Skills & Experience
- 6–8 years of overall IT experience with strong focus on AI, Machine Learning, Data Science, and Generative AI solutions.
- Proven, hands-on experience in:
- Machine Learning model development and deployment
- NLP, Deep Learning, and Generative AI solutions
- LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or equivalent
- RAG architectures, Vector Databases, Prompt Engineering, and AI Agents
- Python, ML frameworks (Scikit-Learn, TensorFlow, PyTorch)
- MLOps and AI deployment practices
- Strong experience in AI opportunity assessments and AI adoption strategies.
- Demonstrated experience delivering AI transformation initiatives from ideation through production deployment.
- Experience building enterprise AI applications, copilots, intelligent assistants, and automation solutions.
- Good understanding of AI governance, Responsible AI, security, compliance, and model monitoring.
- Strong client-facing consulting skills with the ability to present recommendations and technical solutions.
- Excellent communication, presentation, and documentation skills.
Good to Have
- Advanced certifications in AI, Data Science, Cloud AI, or Enterprise Architecture.
- Hands-on experience with Azure AI Foundry, Azure Machine Learning, Databricks, or equivalent AI platforms.
- Experience with LangChain, Semantic Kernel, AutoGen, CrewAI, or other agentic AI frameworks.
- Exposure to knowledge management, enterprise search, and intelligent document processing solutions.
EY | Building a better working world
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
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